최신 DP-900 Korean 무료덤프 - Microsoft Azure Data Fundamentals (DP-900 Korean Version)

Explanation:
A key mechanism that allows Azure Data Lake Storage Gen2 to provide file system performance at object storage scale and prices is the addition of a hierarchical namespace. This allows the collection of objects/files within an account to be organized into a hierarchy of directories and nested subdirectories in the same way that the file system on your computer is organized. With a hierarchical namespace enabled, a storage account becomes capable of providing the scalability and cost-effectiveness of object storage, with file system semantics that are familiar to analytics engines and frameworks.
Reference:
https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-namespace

Explanation:
Semi-structured data (e.g., JSON, CSV, XML) is the bridge between structured and unstructured data. It does not have a predefined data model and is more complex than structured data, yet easier to store than unstructured data.
Reference:
https://www.ibm.com/cloud/blog/structured-vs-unstructured-data

Explanation:
https://learn.microsoft.com/en-us/power-bi/create-reports/desktop-upload-desktop-files

Explanation:
A key mechanism that allows Azure Data Lake Storage Gen2 to provide file system performance at object storage scale and prices is the addition of a hierarchical namespace. This allows the collection of objects/files within an account to be organized into a hierarchy of directories and nested subdirectories in the same way that the file system on your computer is organized. With a hierarchical namespace enabled, a storage account becomes capable of providing the scalability and cost-effectiveness of object storage, with file system semantics that are familiar to analytics engines and frameworks.
One advantage of hierarchical namespace is atomic directory manipulation: Object stores approximate a directory hierarchy by adopting a convention of embedding slashes (/) in the object name to denote path segments.
Reference:
https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-namespace

Explanation:
Data analysts: explore and analyze data to create visualizations and charts that enable organizations to make informed decisions.
https://learn.microsoft.com/en-us/training/modules/explore-roles-responsibilities-world-of-data/2- explore-job-roles

Explanation:
https://docs.microsoft.com/en-us/azure/databricks/scenarios/what-is-azure-databricks
https://docs.microsoft.com/en-us/azure/analysis-services/analysis-services-overview
https://docs.microsoft.com/en-us/azure/data-factory/introduction

Explanation:
https://en.wikipedia.org/wiki/Table_(database)
https://en.wikipedia.org/wiki/View_(SQL)
https://en.wikipedia.org/wiki/Database_index

설명: (DumpTOP 회원만 볼 수 있음)

Explanation:
Streaming is synonymous with low latency (usually fractions of a second). 24 hour interval/latency does not constitute streaming in this scenario.

Explanation:
Azure Data Explorer: KQL (Kusto Query Language), which is a proprietary query language specifically designed for Azure Data Explorer. It is used to analyze and query large volumes of structured and unstructured data in real-time.
Azure Stream Analytics: SQL, which is a standard query language for relational databases. It is used to analyze and process high-velocity, real-time streaming data from various sources, such as IoT devices, social media platforms, and other real-time data streams.
Azure Synapse Analytics: SQL and Python. SQL is used to query and analyze structured data stored in Azure Synapse Analytics, while Python can be used for data preprocessing, machine learning, and other data science tasks.

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Explanation:
Clustered indexes sort and store the data rows in the table or view based on their key values.
These are the columns included in the index definition. There can be only one clustered index per table, because the data rows themselves can be stored in only one order.

Explanation:
SQL Server on Azure VM falls into the industry category Infrastructure-as-a-Service (IaaS) and allows you to run SQL Server inside a fully managed virtual machine (VM) in Azure.
The most significant difference from SQL Database and SQL Managed Instance is that SQL Server on Azure Virtual Machines allows full control over the database engine. You can choose when to start maintenance/patching, change the recovery model to simple or bulk-logged, pause or start the service when needed, and you can fully customize the SQL Server database engine.
With this additional control comes the added responsibility to manage the virtual machine.
Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/azure-sql-iaas-vs-paas-what-is- overview?view=azuresql

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Explanation:
Box 1: Diagnostic
Diagnostic Analytics: At this stage you can begin to answer some of those why questions.
Historical data can begin to be measured against other data to answer the question of why something happened in the past. This is the process of gathering and interpreting different data sets to identify anomalies, detect patters, and determine relationships.
Box 2: Prescriptive
Prescriptive analytics is a combination of data, mathematical models, and various business rules to infer actions to influence future desired outcomes.
Incorrect Answer:
Predictive analytics, broadly speaking, is a category of business intelligence that uses descriptive and predictive variables from the past to analyze and identify the likelihood of an unknown future outcome Box 3: Cognitive Reference:
https://demand-planning.com/2020/01/20/the-differences-between-descriptive-diagnostic-predictive-cognitive-analytics/
https://azure.microsoft.com/en-us/blog/answering-whats-happening-whys-happening-and-what-will-happen-with-iot-analytics/

Explanation:
Box 1: Tree map
Treemaps are chart of colored rectangles, with size representing value. They can be hierarchical, with rectangles nested within the main rectangles.

Box 2: Key influencer
A key influencer chart displays the major contributors to a selected result or value.
Box 3: Scatter
Scatter and Bubble charts display relationships between 2 (scatter) or 3 (bubble) quantitative measures -- whether or not, in which order, etc.
https://docs.microsoft.com/en-us/learn/modules/explore-concepts-of-data-analytics/3-explore- data-visualization